A cognitive taxonomy of medical errors

Jiajie Zhang, Vimla L. Patel, Todd R. Johnson, Edward H. Shortliffe

Research output: Contribution to journalArticlepeer-review

175 Scopus citations


Objective. Propose a cognitive taxonomy of medical errors at the level of individuals and their interactions with technology. Design. Use cognitive theories of human error and human action to develop the theoretical foundations of the taxonomy, develop the structure of the taxonomy, populate the taxonomy with examples of medical error cases, identify cognitive mechanisms for each category of medical error under the taxonomy, and apply the taxonomy to practical problems. Measurements. Four criteria were used to evaluate the cognitive taxonomy. The taxonomy should be able (1) to categorize major types of errors at the individual level along cognitive dimensions, (2) to associate each type of error with a specific underlying cognitive mechanism, (3) to describe how and explain why a specific error occurs, and (4) to generate intervention strategies for each type of error. Results. The proposed cognitive taxonomy largely satisfies the four criteria at a theoretical and conceptual level. Conclusion. Theoretically, the proposed cognitive taxonomy provides a method to systematically categorize medical errors at the individual level along cognitive dimensions, leads to a better understanding of the underlying cognitive mechanisms of medical errors, and provides a framework that can guide future studies on medical errors. Practically, it provides guidelines for the development of cognitive interventions to decrease medical errors and foundation for the development of medical error reporting system that not only categorizes errors but also identifies problems and helps to generate solutions. To validate this model empirically, we will next be performing systematic experimental studies.

Original languageEnglish (US)
Pages (from-to)193-204
Number of pages12
JournalJournal of Biomedical Informatics
Issue number3
StatePublished - Jun 2004
Externally publishedYes

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics


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